About Me

Here is Yuhan Qiao (John, 乔禹涵). I received my Master’s degree in Computer Science & Technology from Beijing JiaoTong University in 2024, supervised by Prof. Caiyan Jia. Before that, I obtained my Bachelor’s degree in Infomation Engineering from China University of Mining & Technology (Beijing).

My previous research focused on graph representation learning with an emphasis on improving model generalization and robustness through self-supervised and semi-supervised learning approaches. Specifically, I explored applying these methods to the task of rumor (misinformation) detection, where labled rumor data is often scarce.

To address this challenge, I proposed a self-training framework aided by graph self-supervised pre-training, which enables joint learning from labeled and unlabeled rumor data and achieves significant performance improvements at low cost. This work was published in Neurocomputing in 2024, titled “A Debiased Self-Training Framework with Graph Self-Supervised Pre-training Aided for Semi-Supervised Rumor Detection.” This work also forms the core of my master’s thesis, which further explores the role of self-supervised pre-training in graph-based rumor detection.

Currently, I am taking a gap year to further prepare for my Ph.D. studies, and I am actively seeking a position where I can continue advancing my academic career. I aspire to pursue my doctoral studies abroad to broaden my academic horizons, collaborate with outstanding researchers, and unlock my full research potential—a goal that has long been my dream.

To work toward this goal, I have dedicated significant effort to improving my English proficiency. Over the past year after graduation, I studied intensively for the TOEFL exam and took it four times, eventually achieving a score of 106 (Reading 30, Listening 26, Speaking 23, Writing 27).

Honestly, I consider myself a dedicated, reliable, and steady person with strong perseverance and a never-give-up attitude. I am always open to learning new knowledge and believe in continuous lifelong learning. I hope to find a Ph.D. supervisor whose research interests align with mine and whose personality is compatible, so that we can work together at the forefront of research. I am eager to begin my doctoral journey as soon as possible and continue growing as a researcher.

If you are interested in any aspect of me, I am always open to discussions. Feel free to contact me at yuhan.qiao.bjtu@gmail.com

Research Interests

• Graph Representation Learning
• Misinformation/Rumor/Fake News Detection
• Semi-supervised/Self-Supervised Learning

News and Updates

• Oct 2025：I am currently seeking Ph.D. opportunities worldwide!
• Oct 2025：My personal academic website is now online!